Nielsen’s Twitter TV Ratings Now Identify The Age And Gender Of Those Tweeting About TV (Or Just Lurking)

Measurement firm Nielsen is expanding the type of information it provides for its Twitter TV Ratings service this morning, with the launch of demographic data. This new feature, delivered overnight for over 250 U.S. TV networks, will allow the industry to identify the age and gender of those who are both tweeting about various TV shows and events, as well as those who are viewing those tweets.

Twitter users will be broken down into several “age buckets,” the firm says, including the following: ages 13-17, 18-24, 25-34, 35-54 and 55+, as well as a general “adult” range of 18-49. The company says that already, some initial analysis of Twitter TV demographics across some 273 broadcast and cable program episodes reveals that there is a fairly broad age and gender distribution across programming already.

In earlier research, Nielsen found that not only do more people read tweets about TV rather than create them (viewers outnumber authors by a 50-1 margin, says Nielsen), but those tweet viewers tend to represent a more demographically balanced profile than those creating the tweets.

Explains Nielsen, “for example, a program where Twitter TV Authors [as it calls those writing tweets] are 80 percent male may have a Twitter TV Audience that is that is 60 percent female. This indicates that Twitter TV can be used as an important tool to reach audiences beyond a program’s core viewership.” This broader tweet-viewing demographic could also mean that TV shows whose audience skews older could reach a younger audience by nature of the tweets viewed by Twitter users.

In the initial study of Twitter TV demographics, Nielsen found that Twitter TV Authors for the episodes analyzed ranged from 12 percent male to 92 percent male, which means the Twitter platform itself isn’t necessarily skewing more male or female, but each type of show being tweeted about draws in a different type of audience.

The program episode skewing oldest counted 85 percent of its Twitter TV Authors above the age of 35, while 98 percent of the Twitter Authors for the youngest-skewing program were below the age of 35, said Nielsen in detailing these findings further. In addition, on average, the Twitter TV Authors for Sports Events skewed 79 percent male, while Reality programs skewed 65 percent female. Reality programs also had a younger mix of Twitter TV Authors: 75 percent were below the age of 35. Meanwhile, 63 percent of Authors were below 35 for Comedy programs.

The company says the ability to view the demographic data from TV-related tweets will now be delivered overnight for programming across the supported networks at the at the episode, program, network, and total TV levels.

Network, agency, and advertiser clients can access Demographics for Nielsen Twitter TV Ratings through Nielsen SocialGuide Intelligence (NSGI), including its API, and Nielsen National Television View (NNTV).

Nielsen first its TV Ratings feature in partnership with Twitter in late 2012, positioning its as a tool that advertisers could use to create campaigns targeting specific Twitter customers, as well as a tool ad execs could use to help identify TV shows with lower ratings but a core group of heavily engaged fans. Twitter could also help producers figure out how their audience is responding to shows, and why some episodes drew in more viewers than others.

We’ve asked Nielsen to clarify how it’s extracting the demographic data from Twitter’s platform, given that Twitter requires little personal information in order for users to establish accounts, meaning that it can be used as a nearly-anonymous service, if someone wanted to go that route. (That is, there’s no need to use a “real name,” as on Facebook, or provide your gender or age in your Twitter profile.)

The company explains that it uses a “modeled approach” to collecting this information precisely because Twitter doesn’t require demographic data when users sign up. So instead, the models for deriving demographics are based on a combination of features, including things like the user’s first name, accounts it follows, details found in the bio/profile text, text of the user’s recent tweets, handle and more. Those results are then validated against Nielsen’s Online Panels.